Mathematical modelling of behavior

MATH-463

Lecturer(s) :

Language:

English

Summary

Discrete choice models allow for the analysis and prediction of individuals' choice behavior. The objective of the course is to introduce both methodological and applied aspects, in the field of marketing, transportation, and finance.

Content

MOOC

1. Introduction and examples

2. Choice theory

3. Binary choice

4. Multinomial choice

5. Specification testing

6. Prediction

Ex cathedra lectures

7. Nested Logit model

8. Multivariate extreme Value models

9. Sampling

10. Mixed models.

11. Choice models with latent variables.

Learning Outcomes

By the end of the course, the student must be able to:

Model discrete choice

Transversal skills

Use a work methodology appropriate to the task.

Assess one's own level of skill acquisition, and plan their on-going learning goals.

Use both general and domain specific IT resources and tools

Teaching methods

Lectures:

The first half of the semester is based on the online MOOC "Introduction to discrete choice models". There is no lecture in class.

The second half of the semester is based on ex-cathedra lectures in class.

Exercices and laboratories:

They are organized every week during the semester. The students will estimate the parameters of behavioral models based on real data.

Expected student activities

Every week, the students are supposed to

read the appropriate material, according to the schedule (the material for a given week is supposed to be read before the lecture of that week);